Posted on 01/10/2022 1:28:57 PM PST by hamburger hill
The Militant Public Health Establishment can only forge ahead on the shoulders of their lie. To admit failure is not an option. That would or could result in massive class-action lawsuits – despite immunity for Big Pharma because of the complete lack of honesty and transparency.
(Excerpt) Read more at granitegrok.com ...
Little anecdotal observation: Several vaxxed and boosted friends all came down with the bug over New Years. Nearly all of them younger than me, and some in better shape. I came down with it too, as a PureBlood, and I was down for a whopping 2 days. None of my friends fared as well as I, and some of my boosted friends are still recovering today.
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I know it’s purely anecdotal but one of my kids had a fender bender in early December and our national case count began increasing, on an accelerating rate, after that.
She, of course, denies responsibility for causing the surge and claims it’s pure coincidence BUT WE KNOW BETTER, DON’T WE!
Why is this excerpted, if from a blog?
Let me guess.. mass formation?
Kyle A. Beattie is a Political Science PhD student with a focus on corruption studies.
I don't know about you but when I have serious epidemiological questions I go straight to Poli Sci students.
They know most everything.
Waiting for the democrat/media/big pharma/Faux-xi cheerleaders on here to say the death serum is perfectly safe with 98% efficacy.
Oh my.
Numbers are numbers and statiscal analsysis does not depend on vaxx or anti vaxx orientation, but an honest analysis of the data. Unless you have an agenda, then shoot the messanger and facts be damned. And attack the messenger.
Wonder where the vax shills are.
A statistical analysis is only as good as the assumptions underlying it, and while I'm not an epidemiologist either even I can see glaring holes in Beattie's effort.
Among other issues, the background prevalence of the disease isn't even considered.
We know Covid has hit countries in waves and there's been a very uneven distribution of cases over time.
In particular, many countries saw their biggest waves associated with Delta (until Omicron), which came later in the cycle and corresponded with higher vaccination rates. So he basically says - "look, vaccinations went up and so did cases. Must have been the vaccine."
Here's what he says in the paper:"...this allows us to look at the past 12-16 months (each country is slightly different) before vaccine administration began, this is called the pre-intervention period, and utilize that data to project where y1 (total deaths per million) and y2 (total cases per million) would have been had the intervention of X (vaccine administration) not occurred, what the authors call a “counterfactual”"
Even I can see the obvious flaw here. He's looking back up to 16 months, when the epidemic was in its early stages or hadn't even started yet and uses this time period to predict what the case and death rates should be going forward. This would make sense if cases and deaths were random events, which is where Bayesian analysis could be useful, but obviously they aren't random.
They're driven by the waves of virus circulating around the world and there's no way looking back can help predict what's going to happen next in a pandemic.
The type of analysis he's doing appears to be totally inappropriate for what he's trying to analyze.
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